Precision feeding system for largemouth bass (Micropterus salmoides) based on multi-factor comprehensive control

Abstract

In order to solve a series of problems in the current feeding process, such as inaccuracy, unevenness and high labour costs, a precision feeding system for largemouth bass was developed by integrating feeding management model, water quality monitoring system, fish feeding activity sensor, automatic feeding machine and software platform. Based on the analysis of the growth data of largemouth bass and the bioenergetics principle, the feeding management model for predicting the growth, feed requirements and waste output of largemouth bass was constructed and validated under different culture modes. The real-time DO parameters were used to fine-tune the feed requirements predicted by the model. The feed requirements were then further precisely adjusted by combining the intensity of fish feeding activities. The web platform client used supported the access of any browser and provided a visual interface for software users. The experimental results showed that the feeding management model provides reliable estimates of growth, feed requirements and waste output for largemouth bass. The function of dynamically adjusting the model and feeding parameters through feedback and production data provided by cloud serves or users improved the application effectiveness and scope of the system. The system comprehensively considered multiple factors such as fish biological characteristics, physiological stages, feed nutrients composition, environmental factors and fish appetite, and incorporated relevant technologies or equipment to provide an effective tool for users to shift from experience-driven to knowledge-driven approaches to better optimise production and feeding, thereby improving the economic benefits and environmental sustainability of aquaculture.